Created
January 7, 2018 13:54
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Explore TB mortality excluding HIV using getTBinR
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# install.packages("getTBinR") | |
library(getTBinR) | |
# install.packages("tidyverse") | |
library(tidyverse) | |
# Get the data | |
tb_burden <- get_tb_burden(download_data = TRUE, save = TRUE) | |
dict <- get_data_dict(download_data = TRUE, save = TRUE) | |
# Look up variables with mortality in their definition | |
search_data_dict(def = "mortality") | |
# Map mortality excluding HIV | |
map_tb_burden(metric = "e_mort_exc_tbhiv_100k") | |
# Get countries with highest TB mortality (exc HIV) in the data | |
high_mortality_countries <- tb_burden %>% | |
group_by(country) %>% | |
summarise(e_mort_exc_tbhiv_100k = max(e_mort_exc_tbhiv_100k)) %>% | |
ungroup %>% | |
arrange(desc(e_mort_exc_tbhiv_100k)) %>% | |
slice(1:10) %>% | |
pull(country) %>% | |
unique | |
# Overview of 10 countries with highest TB mortality rates (exc HIV) | |
plot_tb_burden_overview(metric = "e_mort_exc_tbhiv_100k", | |
countries = high_mortality_countries) | |
# Trends over time in mortality rates (exc HIV) by country | |
plot_tb_burden(metric = "e_mort_exc_tbhiv_100k", | |
countries = high_mortality_countries, | |
facet = "country", scales = "free_y") | |
# Trends over time in incidence rates by country for countries with highest TB mortality (exc HIV) | |
plot_tb_burden(countries = high_mortality_countries, | |
facet = "country", scales = "free_y") |
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